Raghu Pasupathy

60 papers A* 1Misc 35Journal 24

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Near-Optimal Private Tests for Simple and MLR Hypotheses. CoRR Yu-Wei Chen, Raghu Pasupathy, Jordan Awan
2025	J	`jnl`	A Retrospective Approximation Approach for Smooth Stochastic Optimization. Math. Oper. Res. David Newton, Raghu Bollapragada, Raghu Pasupathy, Nung Kwan Yip
2025	J	`jnl`	Complexity of Zeroth- and First-Order Stochastic Trust-Region Algorithms. SIAM J. Optim. Yunsoo Ha, Sara Shashaani, Raghu Pasupathy
2025	A*	`conf`	Optimal Survey Design for Private Mean Estimation. ICML Yu-Wei Chen, Raghu Pasupathy, Jordan Awan
2025	J	`jnl`	Optimal Survey Design for Private Mean Estimation. CoRR Yu-Wei Chen, Raghu Pasupathy, Jordan Awan
2025	J	`jnl`	Uncertainty quantification using simulation output: batching as an inferential device. J. Simulation Yongseok Jeon, Yi Chu, Raghu Pasupathy, Sara Shashaani
2024	J	`jnl`	Complexity of Zeroth- and First-order Stochastic Trust-Region Algorithms. CoRR Yunsoo Ha, Sara Shashaani, Raghu Pasupathy
2024	Misc	`conf`	Introduction to Optimal Transport. WSC Ilya O. Ryzhov, Raghu Pasupathy, Harsha Honnappa
2024	J	`jnl`	Overlapping Batch Confidence Intervals on Statistical Functionals Constructed from Time Series: Application to Quantiles, Optimization, and Estimation. ACM Trans. Model. Comput. Simul. Ziwei Su, Raghu Pasupathy, Yingchieh Yeh, Peter W. Glynn
2023	Misc	`conf`	Bootstrapping And Batching For Output Analysis. WSC Raghu Pasupathy
2023	J	`jnl`	Overlapping Batch Confidence Intervals on Statistical Functionals Constructed from Time Series: Application to Quantiles, Optimization, and Estimation. CoRR Ziwei Su, Raghu Pasupathy, Yingchieh Yeh, Peter W. Glynn
2022	J	`jnl`	Adaptive Sampling line search for local stochastic optimization with integer variables. Math. Program. Prasanna K. Ragavan, Susan R. Hunter, Raghu Pasupathy, Michael R. Taaffe
2022	Misc	`conf`	Central Limit Theorems for Constructing Confidence Regions in Strictly Convex Multi-Objective Simulation Optimization. WSC Susan R. Hunter, Raghu Pasupathy
2022	Misc	`conf`	Overlapping Batch Confidence Regions on the Steady-State Quantile Vector. WSC Raghu Pasupathy, Dashi I. Singham, Yingchieh Yeh
2022	Misc	`conf`	Sample Average Approximation Over Function Spaces: Statistical Consistency and Rate of Convergence. WSC Zihe Zhou, Harsha Honnappa, Raghu Pasupathy
2021	J	`jnl`	Adaptive Sequential Sample Average Approximation for Solving Two-Stage Stochastic Linear Programs. SIAM J. Optim. Raghu Pasupathy, Yongjia Song
2020	J	`jnl`	Adaptive Sequential SAA for Solving Two-stage Stochastic Linear Programs. CoRR Raghu Pasupathy, Yongjia Song
2020	J	`jnl`	Multi-objective ranking and selection: Optimal sampling laws and tractable approximations via SCORE. J. Simulation Eric A. Applegate, Guy Feldman, Susan R. Hunter, Raghu Pasupathy
2020	Misc	`conf`	Risk-Efficient Sequential Simulation Estimators. WSC Raghu Pasupathy, Yingchieh Yeh
2019	Misc	`conf`	Astro for Derivative-Based Stochastic Optimization: Algorithm Description & Numerical Experiments. WSC Daniel Vasquez, Raghu Pasupathy, Sara Shashaani
2019	Misc	`conf`	Redesigning a Testbed of Simulation-Optimization Problems and Solvers for Experimental Comparisons. WSC David J. Eckman, Shane G. Henderson, Raghu Pasupathy
2019	Misc	`conf`	The Number of Random Restarts Required to Identify all Solutions to a Nonlinear System: Applications to Global Stochastic Optimization. WSC Raghu Pasupathy
2018	J	`jnl`	ASTRO-DF: A Class of Adaptive Sampling Trust-Region Algorithms for Derivative-Free Stochastic Optimization. SIAM J. Optim. Sara Shashaani, Fatemeh Sadat Hashemi, Raghu Pasupathy
2018	J	`jnl`	On Sampling Rates in Simulation-Based Recursions. SIAM J. Optim. Raghu Pasupathy, Peter W. Glynn, Soumyadip Ghosh, Fatemeh Sadat Hashemi
2018	Misc	`conf`	Optimal Allocations for sample Average Approximation. WSC Prateek Jaiswal, Harsha Honnappa, Raghu Pasupathy
2018	Misc	`conf`	Recent Trends in stochastic Gradient Descent for Machine Learning and Big Data. WSC David Newton, Raghu Pasupathy, Farzad Yousefian
2017	Misc	`conf`	Phantom pareto systems for multi-objective ranking and selection. WSC Eric A. Applegate, Susan R. Hunter, Guy Feldman, Raghu Pasupathy
2016	Misc	`conf`	ASTRO-DF: Adaptive sampling trust-region optimization algorithms, heuristics, and numerical experience. WSC Sara Shashaani, Susan R. Hunter, Raghu Pasupathy
2015	J	`jnl`	A Stochastic Dilemma Zone Protection Algorithm Based on the Vehicles' Trajectories. J. Intell. Transp. Syst. Pengfei Li, Montasir Abbas, Raghu Pasupathy
2015	Misc	`conf`	Modeling dependence in simulation input: the case for copulas. WSC Raghu Pasupathy, Kalyani Nagaraj
2015	Misc	`conf`	Multi-objective simulation optimization on finite sets: optimal allocation via scalarization. WSC Guy Feldman, Susan R. Hunter, Raghu Pasupathy
2015	Misc	`conf`	Multi-objective simulation optimization on finite sets: optimal allocation via scalarization. WSC Guy Feldman, Susan R. Hunter, Raghu Pasupathy
2014	Misc	`conf`	On adaptive sampling rules for stochastic recursions. WSC Fatemeh Sadat Hashemi, Soumyadip Ghosh, Raghu Pasupathy
2014	J	`jnl`	Stochastically Constrained Ranking and Selection via SCORE. ACM Trans. Model. Comput. Simul. Raghu Pasupathy, Susan R. Hunter, Nugroho Artadi Pujowidianto, Loo Hay Lee, Chun-Hung Chen
2013	J	`jnl`	Integer-Ordered Simulation Optimization using R-SPLINE: Retrospective Search with Piecewise-Linear Interpolation and Neighborhood Enumeration. ACM Trans. Model. Comput. Simul. Honggang Wang, Raghu Pasupathy, Bruce W. Schmeiser
2013	Misc	`conf`	Low-storage online estimators for quantiles and densities. WSC Soumyadip Ghosh, Raghu Pasupathy
2013	J	`jnl`	Optimal Sampling Laws for Stochastically Constrained Simulation Optimization on Finite Sets. INFORMS J. Comput. Susan R. Hunter, Raghu Pasupathy
2013	Misc	`conf`	R-SPLINE for local integer-ordered simulation optimization problems with stochastic constraints. WSC Kalyani Nagaraj, Raghu Pasupathy
2012	Misc	`conf`	Averaging and derivative estimation within stochastic approximation algorithms. WSC Fatemeh Sadat Hashemi, Raghu Pasupathy
2012	J	`jnl`	C-NORTA: A Rejection Procedure for Sampling from the Tail of Bivariate NORTA Distributions. INFORMS J. Comput. Soumyadip Ghosh, Raghu Pasupathy
2012	Misc	`conf`	Closed-form sampling laws for stochastically constrained simulation optimization on large finite sets. WSC Nugroho Artadi Pujowidianto, Susan R. Hunter, Raghu Pasupathy, Loo Hay Lee, Chun-Hung Chen
2011	Misc	`conf`	An introspective on the retrospective-approximation paradigm. WSC Raghu Pasupathy
2011	Misc	`conf`	On interior-point based retrospective approximation methods for solving two-stage stochastic linear programs. WSC Soumyadip Ghosh, Raghu Pasupathy
2011	Misc	`conf`	Optimal sampling laws for constrained simulation optimization on finite sets: the bivariate normal case. WSC Susan R. Hunter, Chun-Hung Chen, Raghu Pasupathy, Nugroho Artadi Pujowidianto, Loo Hay Lee, Chee Meng Yap
2011	Misc	`conf`	SimOpt: a library of simulation optimization problems. WSC Raghu Pasupathy, Shane G. Henderson
2011	J	`jnl`	The stochastic root-finding problem: Overview, solutions, and open questions. ACM Trans. Model. Comput. Simul. Raghu Pasupathy, Sujin Kim
2010	J	`jnl`	An Algorithm for Fast Generation of Bivariate Poisson Random Vectors. INFORMS J. Comput. Kaeyoung Shin, Raghu Pasupathy
2010	Misc	`conf`	Large-deviation sampling laws for constrained simulation optimization on finite sets. WSC Susan R. Hunter, Raghu Pasupathy
2010	J	`jnl`	On Choosing Parameters in Retrospective-Approximation Algorithms for Stochastic Root Finding and Simulation Optimization. Oper. Res. Raghu Pasupathy
2010	Misc	`conf`	Root finding via DARTS - Dynamic Adaptive Random Target Shooting. WSC Raghu Pasupathy, Bruce W. Schmeiser
2010	Misc	`conf`	Selecting small quantiles. WSC Raghu Pasupathy, Roberto Szechtman, Enver Yücesan
2010	Misc	`conf`	The initial transient in steady-state point estimation: Contexts, a bibliography, the mse criterion, and the MSER statistic. WSC Raghu Pasupathy, Bruce W. Schmeiser
2009	J	`jnl`	Retrospective-approximation algorithms for the multidimensional stochastic root-finding problem. ACM Trans. Model. Comput. Simul. Raghu Pasupathy, Bruce W. Schmeiser
2007	Misc	`conf`	A method for fast generation of bivariate Poisson random vectors. WSC Kaeyoung Shin, Raghu Pasupathy
2007	J	`jnl`	Optimal Reconstruction Periods for Stochastically Deteriorating Infrastructures. Comput. Aided Civ. Infrastructure Eng. Raghu Pasupathy, Samuel Labi, Kumares C. Sinha
2006	Misc	`conf`	A testbed of simulation-optimization problems. WSC Raghu Pasupathy, Shane G. Henderson
2006	Misc	`conf`	On choosing parameters in retrospective-approximation algorithms for simulation-optimization. WSC Raghu Pasupathy
2004	Misc	`conf`	Retrospective Approximation Algorithms for the Multidimensional Stochastic Root-Finding Problem. WSC Raghu Pasupathy, Bruce W. Schmeiser
2003	Misc	`conf`	Issues on simulation and optimization II: some issues in multivariate stochastic root finding. WSC Raghu Pasupathy, Bruce W. Schmeiser
2003	Misc	`conf`	Queueing network simulation analysis: queueing-network stability: simulation-based checking. WSC Jamie R. Wieland, Raghu Pasupathy, Bruce W. Schmeiser

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.